The ability to localize users as well as to construct spatial traffic densities can significantly enhance a wireless service provider's (WSP's) ability to service its users and intelligently expand their network. For example, the ability to localize a wireless device enables a variety of Location-Based Services (LBS), including 911, maps, weather, nearby shops, directions, gaming, or other services. Knowledge of high-resolution spatial traffic densities can also be used to cost-effectively place new cells as well as provide important general insight about subscriber behavior. One approach for user localization or traffic density estimation is the use of a GPS (Global Positioning Satellite) system, which requires specialized device receivers not available in all mobile devices. Moreover, GPS does not work deep indoors where there is no visibility to the satellite constellation. The use of GPS also raises concerns about device battery life and network signaling overload. Similar difficulties arise in the construction of traffic densities (e.g., average users/area). These are usually derived by aggregating individual localizations over time within a grid of small areas (bins′). If based on GPS, these densities are inaccurate because the available localizations do not include important subsets of the subscriber population, such as indoor users or outdoor users without GPS receivers.
Another approach is radio fingerprinting, which bypasses some of the above difficulties but suffers from other issues. In fingerprinting, the area is first calibrated by creating a radio map of the service area that associates each (or most) locations with its radio characteristics or fingerprint. This map is assembled through field measurements typically taken via extensive walk or drive test. A typical fingerprint consists of the strength and identity of control channels as seen from surrounding cell site transmitters. Other information such as Round Trip Time (RTT) delay may be included but is not always available. After calibration, routine reports of radio characteristics from commercial mobile devices can be used to dictate a location by associating the report with the most similar fingerprint on the radio map. This process bypasses reliance on GPS but suffers from difficulties such as the expense involved in calibration (it is difficult to take measurements inside all buildings) and reduced accuracy (different locations may have similar or even identical fingerprints). Therefore, there is a need for a scheme with improved calibration (training) and improved accuracy for traffic density estimation and localization.